CobraMamba/mamba-gpt-7b-v2
CobraMamba/mamba-gpt-7b-v2 is a 7 billion parameter causal language model fine-tuned from Mistral-7B-v0.1. This model demonstrates strong performance across various benchmarks, achieving an average score of 54.85 on the Open LLM Leaderboard. With an 8192 token context length, it is suitable for general-purpose language generation and understanding tasks.
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CobraMamba/mamba-gpt-7b-v2: A Fine-Tuned Mistral Model
CobraMamba/mamba-gpt-7b-v2 is a 7 billion parameter causal language model, fine-tuned from the robust mistralai/Mistral-7B-v0.1 base model. This iteration focuses on enhancing performance across a range of evaluation subtasks, aiming for strong general-purpose capabilities.
Key Capabilities & Performance
This model has been evaluated on the Open LLM Leaderboard, demonstrating competitive performance:
- Average Score: 54.85
- ARC (25-shot): 61.95
- HellaSwag (10-shot): 83.83
- MMLU (5-shot): 61.74
- TruthfulQA (0-shot): 46.63
- Winogrande (5-shot): 78.45
- GSM8K (5-shot): 17.29
- DROP (3-shot): 34.07
These metrics indicate its proficiency in common reasoning, commonsense, and language understanding tasks. The model supports a context length of 8192 tokens, making it suitable for processing moderately long inputs.
Usage
Developers can easily integrate mamba-gpt-7b-v2 using the Hugging Face transformers library, requiring transformers (v4.34.0 or newer), accelerate, and torch for deployment on GPU-enabled machines.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.